1. Field of the Invention
The present invention relates to an image processing method and an apparatus therefore for performing calibration of the position and orientation of an image pickup device.
2. Description of the Related Art
Conventional methods for calibrating the position and orientation of a camera that is fixed in a predetermined space are well known. According to one method, a plurality of markers with known coordinates in a three dimensional space (hereinafter referred to as “world coordinates”) are photographed by the camera and the position and orientation of the camera is calculated. The position and orientation satisfies the relationship between the world coordinates of the markers and the coordinates of the markers in the photographed image. That is, this calculation solves the perspective n-point (PnP) problem.
In this method, the markers are extracted from the photographed image and are identified using a marker extraction process. This marker extraction process can be performed either automatically, manually or by a combination of both.
Where the marker extraction process is performed manually by the operator, the photographed image is displayed as a still image on a display. Then, the operator clicks the mouse button on the positions of the markers on the displayed image to input image coordinates of the markers.
Where the marker extraction process is performed automatically, image processing is performed for the still image, which is photographed by the camera, by setting and adjusting marker extraction parameters for determining the threshold values of colors for extraction and the sizes of the markers.
However, marker extraction can be impacted by image brightness. When the contrast level of the image is low in accordance with the brightness of a photographed space and a photographing direction, it becomes difficult to identify the markers on the photographed image. It should be noted that appropriate lighting can be performed during photographing. Where the marker extraction process is performed automatically, the marker extraction parameters need to be adjusted. Therefore, much trial and error is required for setting predetermined surroundings for performing good marker extraction process.
Further yet, a known method for automatically extracting markers captures a still image in order to extract the markers. If the markers cannot be properly extracted, the surrounding thereof is changed and photographed again. Then, the marker extraction is repeated. Thus, the marker extraction process needs to be performed repetitively. Where the marker extraction process is manually performed by the operator, a photographed image must be repetitively input so as to make information required for the marker extraction visible for every marker.